Surv {survival} | R Documentation

## Create a Survival Object

### Description

Create a survival object, usually used as a response variable in a model formula.

### Usage

    Surv(time, event)
    or
    Surv(time, time2, event, type=<<see below>>, origin=0)
    is.Surv(x)

### Arguments

`time` | for right censored data, this is the follow up time. For interval data, the first argument is the starting time for the interval.
`x` | any S-PLUS object.
`event` | The status indicator, normally 0=alive, 1=dead. Other choices are T/F (TRUE = death) or 1/2 (2=death). For interval censored data, the status indicator is 0=right censored, 1= event at `time`, 2=left censored, 3=interval censored. Although unusual, the event indicator can be omitted, in which case all subjects are assumed to have an event.
`time2` | ending time of the interval for interval censored or counting process data only. Intervals are assumed to be open on the left and closed on the right, `(start, end]`. For counting process data, `event` indicates whether an event occurred at the end of the interval.
`type` | character string specifying the type of censoring. Possible values are `"right"`, `"left"`, `"counting"`, `"interval"`, or `"interval2"`. The default is `"right"` or `"counting"` depending on whether the `time2` argument is absent or present, respectively.
`origin` | for counting process data, the hazard function origin. This is most often used in conjunction with a model containing time dependent strata in order to align the subjects properly when they cross over from one strata to another.

### Value

An object of class `Surv`. There are methods for `print`, `is.na`, and subscripting survival objects. To include a survival object inside a data frame, use the `I()` function. `Surv` objects are implemented as a matrix of 2 or 3 columns.
In the case of `is.Surv`, a logical value `T` if `x` inherits from class `"Surv"`, otherwise an `F`.

### DETAILS

In theory it is possible to represent interval censored data without a third column containing the explicit status. Exact, right censored, left censored and interval censored observation would be represented as intervals of (a,a), (a, infinity), (-infinity,b), and (a,b) respectively; each specifying the interval within which the event is known to have occurred.

If `type = "interval2"` then the representation given above is assumed, with NA taking the place of infinity. If `type="interval" `event` must be given. If `event` is `0`, `1`, or `2`, the relevant information is assumed to be contained in `time`, the value in `time2` is ignored, and the second column of the result will contain a placeholder.

Presently, the only methods allowing interval censored data are the parametric models computed by `survreg`, so the distinction between open and closed intervals is unimportant. The distinction is important for counting process data and the Cox model.

The function tries to distinguish between the use of 0/1 and 1/2 coding for left and right censored data using `if (max(status)==2)`. If 1/2 coding is used and all the subjects are censored, it will guess wrong. Use 0/1 coding in this case.

### See Also

`coxph`, `survfit`, `survreg`.

### Examples

    data(aml)
    Surv(aml$time, aml$status)

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